By Brendan Cronin, Divisional Vice President of Innovation, Great American Insurance Group
Part 2 of a 3‑Part Series on Future Proofing Your Business for Digital Success.
Without purpose and context data is just noise. Part 1 of this series focused on how to build a strong foundation in your business that allows for future transformation. Now in part 2, we’ll dive deeper into the fuel that powers transformation: your data.
For decades, businesses were built on structured data, usually in the form of a database. It’s very familiar territory, and companies, jobs, and business strategies have been built around managing this form of data. The data resides in ‘systems of record’ and must be accurate. But unstructured data that lives outside of these controlled processes hides valuable insights that can drive clearer decisions and competitive advantage.
Understanding Unstructured Data
Structured data fits neatly into defined tables, fields, and systems, like financial records or CRM entries. Unstructured data doesn’t conform to strict formats. It’s often freeform and scattered across the business. And while it can appear messy on the surface, it’s also incredibly rich and valuable if you know where to look.
Examples include:
- Emails, call logs, and chat transcripts
- Scanned documents and PDFs
- Multimedia files
- Social sentiments and open-ended survey responses
Where it can live in the equipment finance world:
- Origination packages and borrower documentation
- Collateral descriptions and condition reports
- Service, maintenance, and warranty records
- Customer, dealer or vendor correspondence
- Customer satisfaction surveys
- Portfolio review notes
The Strategic Value of Unstructured Data
While structured data tells you what is happening, unstructured data often tells you why.
When analyzed effectively, unstructured data can reveal patterns and insights that traditional data models miss. This can elevate how organizations operate, compete, and innovate.
Example uses of unstructured data:
- Identify root causes of payment delays, customer friction, or equipment underperformance
- Improve underwriting accuracy using insights from inspection notes or historical interactions
- Spotting patterns in maintenance notes or insurance claims to identify emerging asset-level risks
- Tailor customer communication and servicing based on behavior and sentiment – not just account status
- Use historical correspondence and equipment performance trends to anticipate delinquency or residual value shifts
- Automatically categorize and extract data from PDFs or images to reduce manual work
The challenge?
Because of its freeform nature, unstructured data is notoriously difficult to organize and use for insight extraction. Without the right processes and tools, organizations can end up with massive information debt – files spread across shared drives, personal folders, inboxes, and legacy systems.
And that’s where the opportunity gets lost.
Mining Unstructured Data Effectively
To tap into the value of unstructured data, organizations need to be intentional about how they approach it.
- Start with an inventory
Identify what unstructured data you have, where it lives, and who interacts with it. This simple step often reveals hidden inefficiencies and duplication.
- Choose the right tools and platforms
Modern data platforms and AI tools can ingest and analyze unstructured data at scale, turning previously inaccessible information into usable insight. The better the input, the better the output – feeding well-labeled unstructured data into your models significantly increases their accuracy and predictive strength.
- Build internal capabilities or partner for speed
Many organizations jump-start their unstructured data strategy by partnering with external experts who can deliver quick wins. This gives them time to train internally and build routines for autonomy in the long run.
- Create processes that turn insights into action
Insights are only valuable when they influence decisions, workflows, and outcomes. If you do all the heavy lifting to organize your unstructured data, be sure those learnings can be applied to a current project or long-term goal.
Conclusion
Data is at the center of every transformation effort. While structured data will always play a necessary role in systems of record, it’s the unstructured side – rich, complex, and historically underutilized – that often unlocks the greatest competitive advantage. By investing in the tools and processes needed to capture and learn from this data, organizations can surface meaningful insights and move confidently toward a more predictive future.
In Part 3 of this series, we’ll shift from insights to action – outlining five practical steps to help you position your business for digital success in an AI-driven world.
